Neil J. Salkind’s best-selling Statistics for People Who (Think They) Hate Statistics has been helping ease student anxiety around an often intimidating subject since it first published in 2000. Now the bestselling SPSS and Excel versions are joined by a first edition of the text for use with the R software. New co-author Leslie A. Shaw carries forward Neil’s signature humorous, personable, and informative approach. The text guides students through various statistical procedures, beginning with descriptive statistics, correlation, and graphical representation of data, and ending with inferential techniques and analysis of variance.
Features and benefits:
●Lots of support for getting started with R: Included are two introductory chapters on R and on R Studio, plus an appendix on other R packages and resource sites.
●Step-by-step demonstrations of each statistical procedure in R: The authors show how to import the dataset, enter the syntax to run the test, and understand the output.
●Additional resources make it easy to transition to this text, and to R: Code and datasets are available on an accompanying website, which also includes screencast R tutorial videos for students, and PowerPoint slides and additional test questions for instructors.
Part 1. Yippee! I’m in Statistics
1. Statistics or Sadistics? It’s Up to You.
Part 2. Welcome to the Interesting, Flexible, Useful, Fun and (Very) Deep Worlds of R and Rstudio.
2. Here’s Why We Love R and How to Get Started.
3. Using RStudio: Much Easier Than You Think.
Part 3. Sigma Freud and Descriptive Statistics.
4. Computing and Understanding Averages: Means to an End.
5. Understanding Variability: Vive la Difference.
6. Creating Graphs: A Picture Really Is Worth a Thousand Words.
7. Computing Correlation Coefficients: Ice Cream and Crime.
8. An Introduction to Understanding Reliability and Validity: Just the Truth.
Part 3. Taking Chances for Fun and Profit.
9. Hypotheticals and You: Testing Your Questions.
10. Probability and Why It Counts: Fun with a Bell-Shaped Curve.
Part 4. Significantly Different: Using Inferential Statistics.
11. Significantly Significant: What It Means for You and Me.
12. The One-Sample Z-Test: Only the Lonely.
13. t(ea) for Two: Tests Between the Means of Different Groups.
14. t(ea) for Two (Again): Tests Between the Means of Related Groups.
15. Two Groups Too Many? Try Analysis of Variance.
16. Two Too Many Factors: Factorial Analysis of Variance?A Brief Introduction.
17. Testing Relationships Using the Correlation Coefficient: Cousins or Just Good Friends?
18. Using Linear Regression: Predicting the Future.
Part 5. More Statistics! More Tools! More Fun!
19. Chi-Square and Some Other Nonparametric Tests: What to Do When You’re Not Normal.
20. Some Other (Important) Statistical Procedures You Should Know About.